In modern high-volume customer engagement centers (CEC), there are a number of ways communication between a customer service representative (CSR) and a customer can take place. For example, communication in a CEC can take place over the telephone, through email, and text chat, among other known communication methods. Further it is often the case that a customer contact or communication requires a wide variety of communication protocols and resources. It is extremely important for a CEC system to provide CSRs with accurate and helpful guidance for servicing the incoming customer communications routed to them and keeping the customer pleased with the service provided.
There are a number of methods and systems designed to assist in providing guidance to CSRs to assist in servicing the incoming customer communication. Typically, these methods and systems receive initial data regarding the incoming communication and determine how to provide recommendations based on that initial data and a set of static generalized rules. Some systems may save customer sentiment from prior conversations and use prior customer sentiment in conjunction with the initial data to assist in determining the recommendations. However, the customer sentiment in those systems is typically determined at the end of the conversation and is an overall sentiment depiction for the conversation or is a final sentiment depiction at the end of the conversation and is not connected to a particular CSR action, but connected to the conversation as a whole. Further, these known systems do not focus on the customer sentiment to make the recommendation, the sentiment is merely one of many components to be used in the recommendation.
For example, the system may receive an incoming communication from a customer, when determining a recommendation to make to the CSR, the system may determine that the customer's sentiment during the last conversation was a negative sentiment. Therefore, the system may determine that the current interaction should not be routed to the same CSR as the last conversation, or the system may determine that the customer should be offered a discount or some other sort of compensation due to the prior dissatisfactory communication that lead to the negative sentiment.
These systems, however, are not able to provide the CSR with continuous sentiment tracking in real-time throughout the conversation. Further, these systems are not able to correlate specific individual agent responses and actions to the customer's sentiment to teach the system which agent responses/actions result in a sentiment change.